GenomeBits insight into omicron and delta variants of coronavirus pathogen

Differences and correspondence regarding the intrinsic data organisation of complete delta and omicron genome sequences according to its progression along the nucleotide A,C,G,T bases position are analysed. We found a sort of 'ordered' to 'disordered' transition around the S-spike protein region in the curves obtained from finite alternating sum series having independently distributed terms associated with (0,1) binary indicators for the nucleotides. To uncover such underlying features of genome sequences may assist in the development of synthetic proteins.

How parents share and limit their child’s access to information about COVID-19: A mixed methods online survey study

This study aimed to understand the role that parents play in sharing or limiting their child’s access to information about coronavirus disease 2019 (COVID-19). A subset of data from an international mixed methods online survey study was analysed to elucidate the findings from Brazil. An online survey, conducted between April and June 2020, gathered closed and open text views from parents of children aged 7–12 years old. Quantitative data were analysed using descriptive statistics. Qualitative open text data were analysed using the three stages of the Bardin content analysis framework: pre-analysis (data organisation and initial full-content reading); exploration of the material (thematic coding to identify major motifs and develop thematic categories) and interpretation (treating the data as significant and valid). The sample consisted of 112 (89%) mothers and 14 (11%) fathers. The analysis of the parents open text resulted in two categories: ‘How parents share information with their children about COVID-19’ and ‘How parents limit information to their children about COVID-19’. Some parents reported adopting an honest and open approach on how they shared information with their children, whilst some parents chose to minimise their child’s access to information about the pandemic over concerns of the mortality related to COVID-19.

ESCAPE Data Lake

The European-funded ESCAPE project (Horizon 2020) aims to address computing challenges in the context of the European Open Science Cloud. The project targets Particle Physics and Astronomy facilities and research infrastructures, focusing on the development of solutions to handle Exabyte-scale datasets. The science projects in ESCAPE are in different phases of evolution and count a variety of specific use cases and challenges to be addressed. This contribution describes the shared-ecosystem architecture of services, the Data Lake, fulfilling the needs in terms of data organisation, management, and access of the ESCAPE community. The Pilot Data Lake consists of several storage services operated by the partner institutes and connected through reliable networks, and it adopts Rucio to orchestrate data management and organisation. The results of a 24-hour Full Dress Rehearsal are also presented, highlighting the achievements of the Data Lake model and of the ESCAPE sciences.

Database construction for Vietnamese catfish genome

Molecular biological research plays an important role in aquaculture, contributes to the improvement ofbroodstocks efficiently. Recently, with the development of next-generation sequencing (NGS) technology,genomic studies have been rapidly increased, in which data organisation and management hold a crucialposition. After obtaining NGS sequencing data of Vietnamese catfish (Pangasianodon hypophthalmus), wehave analysed and annotated the catfish genome, from which we have constructed a database for efficientusage. The database is built upon open source software following a three-layer model (interface, Web serviceand database) with a convenient interface through Web browsers. Users can look up sequence and annotationdata as well as visualize sequences through the Jbrowse genome browser. This database is important resourcefor functional genome and genetic improvement of the catfish.

GIS and Geovisual Analysis

The term ‘Geographic Information Systems’ (GIS) defines those computerised systems designed to gather, store, manage, visualise and analyse data with a spatial component. While GIS is generally used to refer to software applications created to manage geographic information, in truth GIS are also defined by other key components such as the spatial data being analysed, the hardware and the human component defined by users’ training, experience and decisions (Ballas et al., 2018). All these are key parts of what is known as GIS, and it is why many argue that GIS should be described in terms of a conceptual and methodological framework rather than software in isolation. As such, researchers have developed an academic discipline, Geographic Information Science, aimed at examining and developing data organisation models and computational mechanisms for GIS, including geovisualisation and spatial analysis techniques (Goodchild, 2009).

L’organisation et la gestion de données au cycle 4 : quelles difficultés ?The organization and management of data in cycle 4: what are the challenges?

RésuméNous nous appuyons sur des observations réalisées dans le cadre de la formation initiale des professeurs de mathématiques pour mettre au jour certains problèmes de la profession, en nous centrant sur le cas de l’organisation et de la gestion de données au cycle 4 (élèves de 12-15 ans). Nous mettons en évidence une péjoration du savoir lié à ce secteur, qui conduit à une instabilité de certaines notions et à de nombreuses imprécisions ou inadéquations. Nous dégageons aussi les difficultés qu’ont les professeurs à proposer des situations riches à étudier et à donner à la classe la possibilité de prendre des chemins variés, ce qui va de pair avec l’absence de gestes propres à l’enquête dans leurs praxéologies de direction d’étude.Mots-clés: Enquête, Praxéologies de direction d’étude.AbstractWe draw on observations made in the frame of the initial training of mathematics teachers, aiming to highlight some problems of the profession, with focus on the case of data organisation and data management in cycle 4 in France (12-15-year-old students). We demonstrate a deterioration of the knowledge linked to this sector, that results in instabilities of certain notions as well as many inaccuracies or inadequacies. We also identify the difficulties encountered by professors in proposing rich enough situations to study and in giving the class the opportunity to take a variety of paths, which are in tandem with the absence of actions specific to the investigation in their praxeologies of study direction.Keywords: Investigation, Praxeologies of study direction.

Searching the great metadata timeline

PurposeThe purpose of this paper is to make a systematic review of the library metadata development history listing out the most significant landmarks and influencing events from Thomas Bodley's rules to the latest BIBFRAME architecture, compare their significance and suitability in the modern-day Web environment.Design/methodology/approachFour time divisions were identified, namely pre-1900 era, 1900–1950, post-1950 to pre-Web era and post-Web era based on pre-set information available to the authors regarding catalogue rules. Under these four divisions, relevant information sources regarding the purpose of the study were identified; various metadata standards released at different times were consulted.FindingsLibrary catalogue standards have undergone transitive changes from one form to another primarily influenced by the changing work environment and different forms of resource availability in libraries. Modern-day metadata standards are influenced by the opportunities provided by the World Wide Web towards libraries and work as a suitable base for data organisation at par with Semantic Web standards.Research limitations/implicationsInformation organisation processes have gone towards a more data-centric approach than earlier document-centric nature in current Semantic Web environment. Libraries had to make a move in this process, and modern-day guidelines in this regard bring the possibility of large-scale discovery services through curated information resources.Originality/valueThe study discovers relationships between key events in the course of development of metadata standards and provides suggestions and predictions regarding it's future developments.

ESCAPE prototypes a data infrastructure for open science

The European-funded ESCAPE project will prototype a shared solution to computing challenges in the context of the European Open Science Cloud. It targets Astronomy and Particle Physics facilities and research infrastructures and focuses on developing solutions for handling Exabyte scale datasets. The DIOS work package aims at delivering a Data Infrastructure for Open Science. Such an infrastructure would be a non HEP specific implementation of the data lake concept elaborated in the HSF Community White Paper and endorsed in the WLCG Strategy Document for HL-LHC. The science projects in ESCAPE are in different phases of evolution. While HL-LHC can leverage 15 years of experience of distributed computing in WLCG, other sciences are building now their computing models. This contribution describes the architecture of a shared ecosystem of services fulfilling the needs in terms of data organisation, management and access for the ESCAPE community. The backbone of such a data lake will consist of several storage services operated by the partner institutes and connected through reliable networks. Data management and organisation will be orchestrated through Rucio. A layer of caching and latency hiding services, supporting various access protocols will serve the data to heterogeneous facilities, from conventional Grid sites to HPC centres and Cloud providers. The authentication and authorisation system will be based on tokens. For the success of the project, DIOS will integrate open source solutions which demonstrated reliability and scalability as at the multi petabyte scale. Such services will be configured, deployed and complemented to cover the use cases of the ESCAPE sciences which will be further developed during the project.

An empirical analysis of Brazilian courts law documents using learning techniques

This paper describes a survey on investigating judicial data to find patterns and relations between crime attributes and corresponding decisions made by courts, aiming to find import directions that interpretation of the law might be taking. We have developed an initial methodology and experimentation to look for behaviour patterns to build judicial sentences in the scope of Brazilian criminal courts and achieved results related to important trends in decision making. Neural networks-based techniques were applied for classification and pattern recognition, based on Multi-Layer Perceptron and Radial-basis Functions, associated with data organisation techniques and behavioral modalities extraction.